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As stereoscopic devices become widely used (immersion-based working environments, stereoscopically viewed movies, autostereoscopic screens, etc), exposure to stereoscopic images can become lengthy, and some eyestrain can set in. We propose a method for reducing eyestrain induced by stereoscopic vision. After reviewing sources of eyestrain linked to stereoscopic vision, we will focus on one of these sources: images with high-frequency contents associated with large disparities. We will put forward an algorithm for removing irritating high frequencies in high disparity zones (i.e., for virtual objects appearing far from the real screen level). We will elaborate on our testing protocol to establish that our processing reduces eyestrain caused by stereoscopic vision, both objectively and subjectively. We will subsequently quantify the positive effects of our algorithm on the relief of eyestrain. As our processing alters the visual quality of the virtual world, we propose a new adaptation of our method to remove this drawback by coupling an eye tracking to our original processing to keep visual quality on the focus point.

In stereo research the construction of a dense disparity map is a complicated task when the scene contains a lot of occlusions. In this case in the neighborhood of occlusions, we could consider that the images have a non-stationary behavior. In this paper we propose a new method for computing a dense disparity map using the decomposition of the 2D wavelet transform in four quarters allowing us to find a corresponding pixel in the case of occlusion as well. Our algorithm constructs in each pixel of two images four estimators corresponding to each quarter. The matching of the four wavelet coefficient estimators in the right image with the other four in the left image allow us to construct a dense map disparity map in each pixel of an image.

International audience; Robots are becoming more and more present in our everyday life: they are already used for domestic tasks, for companionship activities, and soon they will be used to assist humans and collaborate with them in their work. Human-robot collaboration has already been studied in the industry, for ergonomics and efficiency purposes, but more from a safety than from an acceptability point of view. In this work, we focused on how people perceive robots in a collaboration task and we proposed to use virtual reality as a simulation environment to test different parameters, by making users collaborate with virtual robots. A simple use case was implemented to compare different robot appearances and different robot movements. Questionnaires and physiological measures were used to assess the acceptability level of each condition with a user study. The results showed that the perception of robot movements depended on robot appearance and that a more anthropomorphic robot, both in its appearance and movements, was not necessarily better accepted by the users in a collaboration task. Finally, this preliminary use case was also the opportunity to guarantee the relevance of using such a methodology -- based on virtual reality, questionnaires and physiological measures --for future studies.

8 pages; International audience; In this paper we study the memorization of user created gestures for 3DUI. Wide public applications mostly use standardized gestures for interactions with simple contents. This work is motivated by two application cases for which a standardized approach is not possible and thus user specific or dedicated interfaces are needed. The first one is applications for people with limited sensory-motor abilities for whom generic interaction methods may not be adapted. The second one is creative arts applications, for which gesture freedom is part of the creative process. In this work, users are asked to create gestures for a set of tasks, in a specific phase, prior to using the system. We propose a user study to explore the question of gesture memorization. Gestures are recorded and recognized with a Hidden Markov Model. Results show that it seems difficult to recall more than two abstract gestures. Affordances strongly improve memorization whereas the use of colocalization has no significant effect.

Stereoscopic devices are widely used (immersion-based working environments, stereoscopically-viewed movies, auto-stereoscopic screens). In some instances, exposure to stereoscopic immersion techniques can be lengthy, and so eye strain sets in. We propose a method for reducing eye strain induced by stereoscopic vision. After reviewing sources of eye strain linked to stereoscopic vision, we focus on one of these sources: images with high frequency content associated with large disparities. We put forward an algorithm for removing the irritating high frequencies in high horizontal disparity zones (i.e., for virtual objects appearing far from the real screen level). We elaborate on our testing protocol to establish that our image processing method reduces eye strain caused by stereoscopic vision, both objectively and subjectively. We subsequently quantify the positive effects of our algorithm on the relief of eye strain and discuss further research perspectives.

International audience; In this paper we evaluate one interaction method and four display techniques for exploring volumetric datasets in virtual reality immersive environments. We propose an approach based on the display of a subset of the volumetric data, as isosurfaces, and an interactive manipulation of the isosurfaces to allow the user to look for local feature in the datasets. We also studied the influence of four different rendering techniques for isosurface rendering in a virtual reality system. The study is based on a search and point task in a 3D temperature field. User precision, task completion time and user movement were evaluated during the test. The study allowed to choose the most suitable rendering mode for isosurface representation, and provided guidelines for data exploration tasks in immersive environments.

978-1-4614-0063-9; This article has a dual aim: firstly to define augmented reality (AR) en- vironments and secondly, based on our definition, a new taxonomy enabling these environments to be classified. After briefly reviewing existing classifica- tions, we define AR by its purpose, ie. to enable someone to create sensory- motor and cognitive activities in a new space combining the real environment and a virtual environment. Below we present our functional taxonomy of AR environments. We divide these environments into two distinct groups. The first concerns the different functionalities enabling us to discover and understand our environment, an augmented perception of reality. The second corresponds to applications whose aim is to create an artificial environment. Finally, more than a functional difference, we demonstrate that it is possible to consider that both types of AR have a pragmatic purpose. The difference therefore seems to lie in the ability of both types of AR to free themselves or not of location in time and space.

This poster presents a novel approach for integrating, as insets, high resolution stereoscopic areas within a wider low resolution stereoscopic image. The objective is to propose ways to increase local resolution in virtual reality systems, with the use of a small number of additional projectors. Our novel approach consists of inserting high resolution areas whose shape depends on the geometry of 3D objects. For comparison purposes, an existing method is implemented, it consists of setting a rectangular high resolution inset. Both methods are implemented in a large screen VR system with active stereoscopy and head tracking. A user study meant to check for shape perception discrepancies between the two methods was performed. Results show that the novel technique does not introduce any perception distortion in shape size.

Brain damage is a major cause of disability that often leads to deficits in Executive Functions (EF) with dramatic consequences on activities of daily living. While rehabilitation approaches of the dysexecutive syndrome are still limited, Virtual Reality (VR) has shown its potential to propose innovative intervention strategies based on ecologically valid functional tasks. The purpose of this paper is to present the design process of the Therapeutic Virtual Kitchen (TVK) in which ecological and adaptable virtual tasks may be configured by the therapists for patients' assessment and rehabilitation. The outcomes of a preliminary test of feasibility among members of our laboratory and Kerpape Rehabilitation Center are reported and discussed.

A grasp exoskeleton actuated by a string-based platform is proposed to provide the force feedback for a user’s hand in human-scale virtual environments. The user of this interface accedes to seven active degrees of freedom in interaction with virtual objects, which comprises three degrees of translation, three degrees of rotation, and one degree of grasping. The exoskeleton has a light and ergonomic structure and provides the grasp gesture for five fingers. The actuation of the exoskeleton is performed by eight strings that are the parallel arms of the platform. Each string is connected to a block of motor, rotary encoder, and force sensor with a novel design to create the necessary force and precision for the interface. A hybrid control method based on the string’s tension measured by the force sensor is developed to resolve the ordinary problems of string-based interface. The blocks could be moved on a cubic frame around the virtual environment. Finally the results of preliminary experimentation of interface are presented to show its practical characteristics. Also the interface is mounted on an automotive model to demonstrate its industrial adaptability.

International audience; In this paper we present a new technique to extract layers in a video sequence. To this end, we assume that the observed scene is composed of several transparent layers, that their motion in the 2D plane can be approximated with an affine model. The objective of our approach is the estimation of these motion models as well as the estimation of their support in the image domain. Our technique is based on an iterative process that integrates robust motion estimation, MRF-based formulation, combinatorial optimization and the use of visual as well as motion features to recover the parameters of the motion models as well as their support layers. Special handling of occlusions as well as adaptive techniques to detect new objects in the scene are also considered. Promising results demonstrate the potentials of our approach.

Toward a successful 3D and textural reconstruction of urban scenes, the use of both single-row based telemetric and photographic data in a same framework has proved to be a powerful technique. A necessary condition to obtain good results is to accurately calibrate the telemetric and photographic sensors together. We present a study of this calibration process and propose an improved extrinsic calibration technique. It is based on an existing technique which consists in scanning a planar pattern in several poses, giving a set of relative position and orientation constraints. The innovation is the use of a more appropriate laser beam distance between telemetric points and the planar target. Moreover, we use robust methods to manage outliers at several steps of the algorithm. Improved results on both theoretical and experimental data are given.

Virtual reality (VR) is mostly used as a technical means of immersing the user in a computer-generated situation where the reality is the model to be perfectly recreated. Trainers often provide supportive explanations by using tutorial situations that do not exactly reproduce reality. Therefore, VR systems should also provide such tutorial situations. In order to address this issue, an intelligent tutorial agent has been designed to support the learning process. The agent is based on a cognitive taxonomy of the trainee's behaviour in the VR context. For each trainee, the agent provides two kinds of tutorial according to his/her knowledge level. The first one consists of modifying the scenario and the second one consists of guiding the trainee. These strategies can be represented by different fidelity levels of virtual environments (e.g. enhancement, simplification). They can be activated by the trainee, by the trainer or automatically. They are specified off-line and continuously modified on-line. An application of this intelligent agent is being implemented in a VR simulation-based training system for SNCF train drivers. The goal of this application is to teach the procedure to control and handle switches on high speed train tracks.

International audience; We have developed a depth map transform algorithm that converts the depth data according to a video image. The algorithm consists of four steps: a depth map analysis, a video image analysis, a depth map and video image relation creation and finally a depth surface transformation depending on the relation established previously. We show how these four steps are performed assuming that the two maps have nearly equal features. This technic is used with nearly compatible depth map and video image in order to create a quite compatible set allowing virtual objects integration in real images. This is an important aspect of augmented reality since it enables the hidden faces calculation of virtual objects in coherence with the video image even when work conditions hinder accurate camera calibration or model of the real scene is not perfectly known